Non-family Shareholder Governance and Green Innovation of Family Firms: A Socio-emotional Wealth Theory Perspective

We draw on socio-emotional wealth (SEW) theory to investigate the influence of non-family shareholder governance (NFSG) on green innovation in family firms. We find that non-family shareholder holding has no significant impact on green innovation, but the directors appointed by non-family shareholders (NFSDAs) significantly promote the implementation of green innovation strategies in family firms. The underlying mechanisms are characterized by NFSG bringing valuable resources and promoting the firm reputation, which further facilitates green innovation. The effect of NFSG is more pronounced for entrepreneurial family firms and family firms located in high institutional efficiency areas. The green professional backgrounds of NFSDAs and having excess NFSDAs also effectively promote green innovation. Finally, green innovation promotes the long-term orientation of family firms. Through this study, we draw on SEW theory to enrich research on NFSG and green innovation in family firms. Our findings can help family firms achieve a solid basis for long-term orientation

Empirical approximation to invariant measures of non-degenerate McKean--Vlasov dynamics

This paper studies the approximation of invariant measures of McKean--Vlasov dynamics with non-degenerate additive noise. While prior findings necessitated a strong monotonicity condition on the McKean--Vlasov process, we expand these results to encompass dissipative and weak interaction scenarios. Utilizing a reflection coupling technique, we prove that the empirical measures of the McKean--Vlasov process and its path-dependent counterpart can converge to the invariant measure in the Wasserstein metric. The Curie--Weiss mean-field lattice model serves as a numerical example to illustrate empirical approximation.Comment: 21 pages, 1 figur

Identifying vital edges in Chinese air route network via memetic algorithm

Due to its rapid development in the past decade, air transportation system has attracted considerable research attention from diverse communities. While most of the previous studies focused on airline networks, here we systematically explore the robustness of the Chinese air route network, and identify the vital edges which form the backbone of Chinese air transportation system. Specifically, we employ a memetic algorithm to minimize the network robustness after removing certain edges hence the solution of this model is the set of vital edges. Counterintuitively, our results show that the most vital edges are not necessarily the edges of highest topological importance, for which we provide an extensive explanation from the microscope of view. Our findings also offer new insights to understanding and optimizing other real-world network systems